The inventive concepts disclosed herein relate generally to the field of display systems. More particularly, embodiments of the inventive concepts disclosed herein relate to an apparatus for and method of adjusting the dynamic range of an input image so that an output image has a dynamic range that is optimized for being displayed on a particular display device.
Displays are utilized in a wide variety of applications including but not limited to medical, military, avionic, entertainment and computing applications. Raw sensor imagery produced by thermal sensors (e.g. infrared devices) typically has high dynamic range that is greater than the dynamic range that can be presented on some display devices. For example, the Rockwell Collins EP-80 Image Generation System produces simulated image sensory data having a high dynamic range that may be higher than some aircraft cockpit simulator display systems are configured to display. Some image generators create imagery having up to 16 bits per pixel while some display systems are only capable of displaying 8 bits per pixel. Sensor devices may use image processing techniques to reduce the dynamic range of high dynamic range sensor imagery, which certain displays may not support, to a lower dynamic range that is more commonly supported by aircraft display systems. For example, some systems adjust the pixel intensities of an image by using image gain and level mechanisms to convert high dynamic range imagery to low dynamic range imagery capable of being viewed on a low dynamic range display device. However, using gain and level mechanisms to adjust pixel intensities often results in discarding or obscuring information outside of certain image intensity ranges by overly saturating the image with a few predominant pixel intensity levels.
Typically, dynamic range compression reduces the number of bits per pixel, or the number of gray levels (e.g., in a grayscale image) that can be shown in an image. Some image processing techniques use histogram equalization to dynamically compress the intensity range of an image from high dynamic range imagery to low dynamic range imagery. Histogram equalization may be used to compress the intensity range of an image by substituting the intensity of each pixel with a new intensity based on certain mathematical relationships. For example, one well known image processing technique that employs histogram equalization is known as Contrast Limited Adaptive Histogram Equalization (“CLAHE”). However, histogram equalization requires large amounts of computing resources (specifically the amount of data required to represent the pixel intensity transfer function(s)) to adjust the dynamic range of an image and can produce unacceptable levels of intensity quantization resulting in images that are blocky, blurry, pixelated, or otherwise having less than ideal image quality and resolution. Intensity quantization is a form of aliasing that occurs when a number of adjacent intensities from the original image are forced to be the same intensity in the output image.
A need exists for a dynamic range optimization system capable of converting high dynamic range images to low dynamic range images using fewer computing resources than current systems. A further need exists for a dynamic range optimization system that provides clearer output images by reducing intensity quantization and preserving all or most of the input image detail.